Abstract
The purpose of this study is to apply the principles of statistical process control (SPC) in the context of patient specific intensity‐modulated radiation therapy (IMRT) QA to set clinic‐specific action limits and evaluate the impact of changes to the multileaf collimator (MLC) calibrations on IMRT QA results. Ten months of IMRT QA data with 247 patient QAs collected on three beam‐matched linacs were retrospectively analyzed with a focus on the gamma pass rate (GPR) and the average ratio between the measured and planned doses. Initial control charts and action limits were calculated. Based on this data, changes were made to the leaf gap parameter for the MLCs to improve the consistency between linacs. This leaf gap parameter is tested monthly using a MLC sweep test. A follow‐up dataset with 424 unique QAs were used to evaluate the impact of the leaf gap parameter change. The initial data average GPR was 98.6% with an SPC action limit of 93.7%. The average ratio of doses was 1.003, with an upper action limit of 1.017 and a lower action limit of 0.989. The sweep test results for the linacs were ‐1.8%,0%, and +1.2% from nominal. After the adjustment of the leaf gap parameter, all sweep test results were within 0.4% of nominal. Subsequently, the average GPR was 99.4% with an SPC action limit of 97.3%. The average ratio of doses was 0.997 with an upper action limit of 1.011 and a lower action limit of 0.981. Applying the principles of SPC to IMRT QA allowed small differences between closely matched linacs to be identified and reduced. Ongoing analysis will monitor the process and be used to refine the clinical action limits for IMRT QA.PACS number: 87.55.Qr
Highlights
Statistical process control (SPC) has been used in industry since the early 1920s to reduce waste and increase the early detection and prevention capabilities of quality control (QC) and quality assurance (QA) systems.[1]. Recently medical physicists have begun to apply the principles of SPC to all facets of the radiation oncology clinical practice.[2]. SPC can be used to identify out-of-control processes and improve a clinic’s intensity-modulated radiation therapy (IMRT) QA program, linac QC program, and overall patient safety.[3,4,5,6,7,8] Using these methods, the medical physicist can create clinic specific QA and QC action limits that are based on realworld data, as opposed to more generic national guidance.[3,4,5,6,7]
In this study we examined the initial application of SPC to our IMRT QA program, the effect of changes made to the QA program, and the longterm stability of the changes
We focused on the gamma pass rate (GPR) and the average ratio between the measured and planned doses
Summary
Statistical process control (SPC) has been used in industry since the early 1920s to reduce waste and increase the early detection and prevention capabilities of quality control (QC) and quality assurance (QA) systems.[1] Recently medical physicists have begun to apply the principles of SPC to all facets of the radiation oncology clinical practice.[2] SPC can be used to identify out-of-control processes and improve a clinic’s intensity-modulated radiation therapy (IMRT) QA program, linac QC program, and overall patient safety.[3,4,5,6,7,8] Using these methods, the medical physicist can create clinic specific QA and QC action limits that are based on realworld data, as opposed to more generic national guidance.[3,4,5,6,7]. In this study we examined the initial application of SPC to our IMRT QA program, the effect of changes made to the QA program, and the longterm stability of the changes
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